The Design And Implementation Of A Filter Of Pornographic Web Images On Mobile Phone

In recent years, with the popularity of the Internet and mobile phones day by day, harmful information, especially pornographic information, spreads through the Internet and the mobile network, resulting in very negative impact on the physical and mental health of minors. The problem arouses more and more concern of society. Up to now there are three major methods for filtering pornographic images and pornographic Web sites, which are filter based on URL that is short for Uniform Resource Locator, filter based on text and filter based on image content. Compared to the first two methods, the adaptability of filter based on image content is wider and its flexibility is higher. The thesis focuses on content-based image filter.Up to September 2010, I found that there were no articles on content-based pornographic image filter for mobile phones in CNKI that is short for China National Knowledge Infrastructure and no software for mobile phones to filtrate pornographic images comes into market in China in search engines.Smart mobile phone based on Windows Mobile 6 operating system and ARM microprocessor is selected as the development platform, and OpenCV which is an open source computer vision library is selected as the development tool of the image-detecting module. After the features of the hardware and software of the smart mobile phone platform are analyzed, appropriate content-based methods for filtering pornographic images are selected. A software framework for filtering pornographic Web images is presented, which is based on LSP that is short for Layered Service Provider. Because the application development of Windows Mobile is similar to that of Windows desktop and OpenCV cannot be directly used on Windows Mobile, software filtering pornographic Web images for the Windows desktop is developed at first in order to facilitate debugging and comparision. The principle of the module hooking network messages is LSP, and the principle of the module on image-detectinging is face detection, white-balance correction, skin detection and SVM that is short for Support Vector Machines. And skin detection includes skin color detection, texture detetion and connected skin region detection. When it is tested on Windows desktop, the software can real-time filter pornographic images on webpages and its accuracy is fairly high. And then OpenCV and the software are both ported to Windows Mobile. Testing result shows that the software can work on a Windows Mobile phone, but because of the hardware limit of average smart mobile phones, the calculation amount of face detection is quite large, and the module on image-detecting is a litte slow.